Non-insulin-based insulin resistance indices predict early neurological deterioration in elderly and middle-aged acute ischemic stroke patients in Northeast China

Insulin resistance (IR) has a strong association with acute ischemic stroke (AIS) occurrence and poor prognosis of afflicted patients. However, the relation between early neurological deterioration (END) risk and IR in elderly and middle-aged patients remains to be thoroughly studied. Here, we investigated the relationship between four indicators of IR and the risk of END in middle-aged patients patients with AIS. The study retrospectively analyzed 1696 elderly and middle-aged patients having AIS between January 2019 and June 2023. Within 7 days of admission, the patients were then stratified relying upon alternations in the National Institutes of Health Stroke Scale. Subsequently, we employed logistic regression analyses for assessing each index correlation with END on the basis of the tertiles of TyG index (TyGI), triglyceride to high-density lipoprotein ratio (TG/HDL), TyG-BMI, alongside IR metabolic score (METS-IR). These four indicators were significantly heightened in the END group (n = 680) in comparison to the non-END group (n = 1016). When grouping using tertiles, the four aforementioned indicators emerged as independent risk factors for END occurrence, whether or not adjusted for confounding factors. The results revealed a progressive elevation in END occurrence risk with the rise in the tertile of each indicator. Finally, we utilized receiver operating characteristic (ROC) curves for assessing the indicators' predictive power. TyG-BMI, TyGI, TG/HDL, and METS-IRs’ area under the curve (AUC) were, respectively, 0.736 (95% CI: 0.712–0.761; P < 0.001), 0. 694 (95% CI: 0.668–0.721; P < 0.001), 0.684 (95% CI: 0.658–0.711; P < 0.001), and 0.722 (95% CI: 0.697–0.747; P < 0.001). IR is associated with END risk in middle-aged AIS patients. TyG-BMI, TyGI, TG/HDL, and METS-IR are independent risk factors of END in elderly and middle-aged AIS patients. Simultaneously, these four IR indicators have significant predictive power for END.

Stroke places an enormous burden on healthcare systems worldwide, as it is the primary reason for morbidity and mortality in the majority of countries 1,2 .Because of the acute onset and narrow treatment window of stroke, a significant proportion of patients experience early neurological deterioration (END), which affects long-term patient outcomes 3,4 , or worse, functional deterioration with age 5 , even when patients seek timely medical attention in the hyperacute or acute phase.As the aging population continues to grow, the burden will escalate over time.Consequently, early detection and treatment of END is essential in elderly and middle-aged patients suffering from acute ischemic stroke (AIS).
Insulin resistance (IR) constitutes an impaired physiological response of the target tissue to insulin stimulation 6 .Besides being the basis for type II diabetes pathogenesis, IR is the prevalent pathophysiology for various metabolic diseases that include ischemic stroke 7 , coronary heart disorder (CHD) 8,9 , and hyperuricemia 10,11 .Being the gold standard for assessing IR, the high insulin-normal glucose clamp represents both an intricate and expensive method 12 , which limits its use in clinical practice 13 .Accordingly, researching simple and efficient proxies is essential.Earlier studies have shown that biochemical test-derived measures, including IR metabolic score (METS-IR), triglyceride-glucose index (TyGI), along triglyceride to high-density lipoprotein ratio (TG/ HDL), can serve as IR level markers [14][15][16][17][18] .Combining body mass index (BMI) with TyG has succeeded in improving IR prediction 19 .In a national prospective cohort study, significant alternations in TyG-BMI were independently correlated with stroke risk in older and middle-aged individuals 20 .However, it is uncertain whether the aforementioned non-insulin-dependent indicators of IR are associated with END development.Accordingly, we investigated the relationship between the aforementioned measures and END using a large clinical cohort of elderly AIS patients.

Study design and participants
This retrospective study analyzed 1696 AIS patients admitted to the Second Hospital of Harbin Medical University between January 2019 and June 2023, with the human ethics committee of the same institution approving this study (NO.KY2023-162).Inclusion criteria: participants must be at least 45 years of age and have a magnetic resonance imaging diagnosis of AIS.Exclusion criteria: patients were severely impaired in consciousness, unable to cooperate with the study, had undergone thrombolysis or mechanical retrieval of a clot, had a tumor, trauma, surgery, hemorrhage, or incomplete data regarding BMI, fasting blood glucose (FBG), and triglyceride (TG).Figure 1 depicts the patient recruitment.

Data collection
Our study obtained clinical data on the admission of AIS patients to this center: sex, age, weight, height, smoking and alcohol status, as well as diabetes mellitus (DM), hypertension (HTN), and CHD history.On the morning of the second day after enrolment, a healthcare professional drew venous blood from the patients in the fasting state.The following parameters for several indicators were immediately recorded: fasting glucose (FPG), c-reactive protein (CRP), homocysteine (HCY), total cholesterol (TC), TGs, low-density lipoprotein (LDL), and HDL.Furthermore, a designated and professionally trained physician daily evaluated the National Institutes of Health Stroke Scale (NIHSS) score to determine END presence or absence.

Definitions
END: NIHSS score ≥ 2 through a week of enrollment in comparison to on enrollment 21 .

Statistical analysis
Statistical analysis was conducted through SPSS 26.0 (IBM Corp, New York, NY, USA).Regarding continuous variables, normality was first evaluated by utilizing the Shapiro-Wilk test, expressing the results as mean ± standard deviation for normality and medians (P25-P75) for non-normality while reporting the categorical variable data as numbers and percentages.The χ 2 test was employed for categorical variables while utilizing the t-test, Mann-Whitney U, and Kruskal-Wallis H tests for continuous variables.The calculation of odds ratios (OR) and 95% confidence intervals (CI) was performed through logistic regression analysis (LRA) to analyze each indicator correlation with END.Each indicator predictive capability of END was determined through receiver operating characteristics (ROC) and area under the curve (AUC).Meanwhile, MedCalc was used for comparison of the differences in AUC of the indicators.The statistical analyses were all two-sided, with P < 0.5 indicating a significant difference.

Ethics approval and consent to participate
The study was conducted in accordance with the Declaration of Helsinki and approved by the Second Affiliated Hospital of Harbin Medical University Ethical Review Committee (NO.KY2023-162).Informed consent was obtained from all patients.

TyG-BMI and END association
Subsequently, we discovered that TyG-BMI exhibited independence as an END development risk factor (P < 0.05) (Table 4).In models 4 and 5, the risk of END was

METS-IR and END association
Table 5 shows that METS-IR was significantly related to heightened END risk and represented an independent END risk factor (P < 0.05).Using group M1 as the reference, in models 7, 8, and 9, END risk in group M3 was www.nature.com/scientificreports/

TG/HDL and END association
Herein, the TG/HDL could also be an independent END risk factor, both as continuous and categorical variables (Table 6).In models 10, 11, and 12, END risk was significantly elevated in group G3 in comparison to groups G1/G2 and was statistically significant in all cases.

Discussion
To our knowledge, our study is the first to examine the impact of four promising IR metrics on END, based on a case with a relatively large sample size.Additionally, we are the initial effort for comparing TG/HDL, TyGI, TyG-BMI, along METS-IR as END risk predictors in middle-aged and older AIS patients.END-common in the acute stroke phase-affects around 10-40% of patients 24 and possesses a direct association with poor long-term outcomes post-stroke 25 .Previous studies have associated body measurements (e.g., BMI and waist circumference) and IR-related measurements with the incidence and prevalence of stroke, which are mutually reinforcing 26,27 .IR induces several metabolic disorders that promote atherosclerotic plaque rupture, constituting an important risk factor for stroke onset and progression 28 .The normoglycemic clamp test-a gold standard for IR-is slow, complex, and relatively expensive, limiting its use in clinical practice 29 .New, simple, and effective alternative indicators are therefore urgently needed.Composite indices, including METS-IR, TyGI, and TG/HDL (derived from routine hematology studies), have been elucidated to be effective proxies for IR levels with a strong correlation with stroke development.
Our study found that the previously mentioned four indicators exhibited the most significantly elevated levels in the END group.When grouped using tertiles, these four indicators represented independent risk factors for END occurrence, whether or not they were adjusted for confounding factors.Furthermore, as the tertile of each measure rose, the risk of END gradually increased.In this way, our study has identified new predictors that www.nature.com/scientificreports/are easy to monitor and can predict END.By monitoring changes in the above indicators, it is hoped that early identification and timely intervention in high-risk groups will reduce the incidence of END.TyG-BMI is a novel infrared marker combined with the anthropometric measure BMI 30 .A large prospective study represented a correlation between TyG-BMI and an elevated stroke risk 26 .Furthermore, a national prospective cohort study manifested that alterations in TyG-BMI were independently linked to the likelihood of having a stroke in elderly and middle-aged individuals.Monitoring long-term fluctuations in TyG-BMI could prove valuable in identifying individuals with a higher stroke risk 20 .However, no research has examined TyG-BMI and END risk correlation; accordingly, we focused on examining this association.Our findings revealed that these two indicators are independently correlated, even following the adjustment for potential confounding variables.Notably, a rise in TyG-BMI is related to an escalation in END risk.Therefore, TyG-BMI can serve as a valuable indicator for promptly identifying END occurrences in elderly and middle-aged AIS patients.
Furthermore, the TyGI constitutes a surrogate IR marker, helping to identify vascular disease early 31,32 , which represented an independent predictor of stroke progression in a study conducted in a large community center in the United States 28 .Besides, our previous research reported that the TyGI was a significant END risk factor with reliable predictive power 33 .Consistently, TyGI has been demonstrated as an independent END development risk factor, with the two highest quartiles having a higher risk than the lowest quartile.
The TG/HDL-an unconventional lipid parameter-has a strong association with cerebrovascular disease, offering innovative insights into the balance between atherogenic and antiatherogenic lipids 34 .A study found a positive association with adverse outcomes in AIS patients having TG/HDL exceeding 3.515 35 .Although no study has correlated this previously mentioned ratio with END, our study elucidated that this ratio could be an independent END predictive factor with a high predictive value that was similar to TyG-BMI and the TyGI.Accordingly, this predictive ability must be confirmed in further studies.
METS-IR, developed by Bello-Chavolla and colleagues 36 , is a novel IR marker that combines glucose and lipid metabolism with the state of nutrition.METS-IR has a close relation to several risk factors for stroke, including DM, obesity, HTN, and atherosclerosis [37][38][39] .An increased METS-IR can help identify people at a higher risk of experiencing a stroke 40 .In addition, it was discovered that METS-IR exhibits a correlation with a higher poor prognosis post-intravenous thrombolysis 41 .Regrettably, METS-IR and END correlation has yet to be studied.Nonetheless, we indicate that METS-IR can predict END occurrence and may be considered an independent

Table 2 .
Early neurological deterioration (END) and risk factor associations.

Table 3 .
TyGI and END association.In comparison to non-END.Early neurological deterioration: END;
a Unadjusted-Model 10. b Age and sex-adjusted Model 11. c

Table 7 .
Performance of four metrics for early neurological deterioration prediction.The area under the curve: AUC; confidence interval: CI.